Skip to content

Task reference

A concise reference for every FLAF task: what it does, what it branches over, and its task-specific parameters. The common parameters (--version, --period, --workflow, --branches, --test, …) apply to all of them and are documented in Command arguments.

Production tasks live in FLAF/AnaProd/tasks.py (invoke as FLAF.AnaProd.tasks.<Name>); analysis tasks live in FLAF/Analysis/tasks.py (invoke as FLAF.Analysis.tasks.<Name>). For the order in which they run, see the walkthrough and data flow.

Production tasks (AnaProd)

InputFileTask

Resolves the concrete list of NanoAOD files for the requested datasets and era, querying Rucio for the file list and their disk availability. Runs locally (it is a LocalWorkflow, not submitted to HTCondor) and is cheap. Every downstream task depends on it, so it runs first.

AnaTupleFileTask

Runs the analysis producer (AnaProd/anaTupleProducer.py, inside CMSSW) over input files to create anaTuples. Branches over input files (one branch per NanoAOD file) — the workflow you most often submit to HTCondor.

AnaTupleFileListBuilderTask / AnaTupleFileListTask

Helper workflows that assemble the lists of per-file anaTuples to be merged. Normally pulled in automatically as dependencies of the merge step; you rarely call them directly.

AnaTupleMergeTask

Merges the per-file anaTuples into one anaTuple per dataset (data merged across runs).

  • Parameter: --delete-inputs-after-merge (bool, default false) — remove the per-file inputs once the merge succeeds, to save space.

Analysis tasks (Analysis)

HistTupleProducerTask

Reads merged anaTuples and computes the analysis observables (the configured "payload producers"), writing histTuples.

HistFromNtupleProducerTask

Fills histograms of the requested variables from the histTuples, including systematic variations. Branches over (dataset, file-chunk): each job reads its chunk of input files once and fills all active variables in a single event-loop pass. Large datasets are parallelized by splitting their files into chunks (work is never split per variable, which would re-read the same events once per variable).

  • Parameters: --variables (string; restrict which variables), --n-files-per-job (int, default 20; input files processed per branch).

HistMergerTask

Merges the per-piece histograms into per-process histograms ready for plotting and fitting. Each branch (one per variable) merges all uncertainty sources in a single pass: every input file is read once and all histograms are written directly to the final output file.

  • Parameter: --variables (string; restrict which variables).

AnalysisCacheTask

Pre-computes a per-event payload that later stages reuse — most importantly the b-tag shape weights in HH→bb̄WW. Pulled in automatically when an analysis needs it.

  • Parameter: --producer-to-run (which cached payload producer to run).
  • Caveat: on a cold cache this can be time-consuming (≈ 1 h per branch). Reuse it across runs via a per-task version override.

AnalysisCacheAggregationTask

Aggregates the cached payloads produced by AnalysisCacheTask into the form the histogram stages consume.

  • Parameter: --producer-to-aggregate.

HistPlotTask

Produces the final plots via the PlotKit submodule (matplotlib + mplhep by default; optional ROOT + cmsstyle). Branches over variables (one branch per variable).

  • Parameter: --variables (string; restrict which variables).

Plot styling comes from the analysis config/plot/*.yaml files (cms_stacked.yaml, histograms.yaml, <era>.yaml) — unchanged from the legacy renderer. Signal overlays are scaled by signal_plot_scale in global.yaml: a fixed factor (e.g. 100) or bkg to normalise each signal's integral to the summed background (shape comparison; the legend then reads … (norm. to bkg)). PlotKit can also render outside FLAF; see its README for the standalone python -m PlotKit.cli entry point.

Statistical-inference tasks

The limit/fit tasks (e.g. PlotResonantLimits, PlotPullsAndImpacts) come from the StatInference and inference/dhi submodules and run inside CMSSW/Combine. They are analysis-specific — see each HH analysis's Statistical inference page (via Analyses) and the walkthrough.

Discover parameters from the command line

law run <Task> --help lists every parameter a task accepts, including the ones inherited from the base classes.